Many situations involving the provision of goods in today's marketplace, such as the provision of fast food meals, are predicated on the ability of a customer to efficiently place an order and receive the meal (or other goods) with the correct food items in a quick and accurate manner.
Human interaction between the customer and the employee leaves room for time-costly mistakes due to either user error or misinterpretation through language barriers, speech impediments or the hard of hearing, inaudible conversation due to faulty drive-thru speakers, etc. These mistakes can lead to fewer return customers due to lower satisfaction ratings stemming from either poor customer service, processing incorrect orders, lengthy wait times, interruptions from implementing new technologies, and so on.
In addition, a point-of-sale/drive-thru transaction is limited in its ability to receive orders and deliver goods by the human factors involved, i.e. the process may only move as fast as the employee can physically work. For example, timing for processing an order is limited by how quickly the employee is able to take the customer's order, listen to the customer's order, record the order, confirm the order, prepare the order, process the payment manually, and deliver the ordered items to the customer. This process is not only taxing on both the employee and the customer, but is also costly for the fast food retailer.
Barcodes or other unique identifiers today aren't dynamic and don't change or generate specific to a customer's order. Identifiers scanned at a fast food restaurant today only link to profiles and a method of payment (scanned at checkout by an employee) only after an order has been placed. The customer still has to communicate their order within the store, at a drive-thru, or preselect a specific store online and preorder ahead of time through the restaurant's mobile application. Orders also cannot be shared, consolidated, or placed in a single, electronic process. Payments also cannot be automatically or electronically split amongst customers.